Optimizing conversions in a Trade-in flow
Optimizing conversions in a Trade-in flow
Prioritizing revenue impact in a scale-up
Conversion optimization
Conversion optimization
Growth design
Optimizing conversions in a Trade-in flow
Prioritizing revenue impact in a scale-up
Conversion optimization
Growth design
Optimizing conversions in a Trade-in flow
Prioritizing revenue impact in a scale-up
Conversion optimization
Growth design
My role:
As the sole designer on this project I owned problem framing, design exploration, stakeholder alignment, and design delivery.
Scope:
I redesigned the entire trade-in flow, but this case study focuses on the drop-off at the offer page.
Results:
14%+
Users passing the offer step
8.4%+
Higher Trade-ins
Results:
14%+
Users passing the offer step
8.4%+
Higher Trade-ins
Industry
E-commerce
Team
Me - PM - Developers
Platforms
Web, mobile & tablet
Timeline
3 months
Industry
E-commerce
Team
Me - PM - Developers
Platforms
Web and mobile
Web, mobile & tablet
Web, mobile & tablet
Timeline
1 month
3 months
Business objective
Increase the number of users completing a trade-in on the website
Process
01
Understanding the problem
Synthesized existing research, behavioral data, and funnel drop-offs.
01
Understanding the problem
Synthesized existing research, behavioral data, and funnel drop-offs.
01
Understanding the problem
Synthesized existing research, behavioral data, and funnel drop-offs.
02
Aligning on a strategy
Partnered with product and engineering to focus on one high-impact, feasible lever.
02
Aligning on a strategy
Partnered with product and engineering to focus on one high-impact, feasible lever.
02
Aligning on a strategy
Partnered with product and engineering to focus on one high-impact, feasible lever.
03
Design and test
Explored multiple concepts, assessed risk and feasibility, and shipped for validation.
03
Design and test
Explored multiple concepts, assessed risk and feasibility, and shipped for validation.
03
Design and test
Explored multiple concepts, assessed risk and feasibility, and shipped for validation.
01
Understanding the problem
Synthesized existing research, behavioral data, and funnel drop-offs.
01
Understanding the problem
Synthesized existing research, behavioral data, and funnel drop-offs.
02
Aligning on a strategy
Partnered with product and engineering to focus on one high-impact, feasible lever.
02
Aligning on a strategy
Partnered with product and engineering to focus on one high-impact, feasible lever.
03
Design and test
Explored multiple concepts, assessed risk and feasibility, and shipped for validation.
03
Design and test
Explored multiple concepts, assessed risk and feasibility, and shipped for validation.
User Problem
Users perceived trade-in offers as unfairly low and dropped off early.
The Trade-in flow had one huge drop-off and that was when users saw the price offered for their clubs.
Visit Trade-in Page
Select club model
View offered price
High drop offs
Cart
Checkout
Existing experience
Key insight: The business already offered a 20% trade-in bonus at checkout, but this incentive was not visible at the offer step.
For example:
Offer step showed $110
Final checkout value was $132
Most users dropped off before knowing the higher value existed
Existing experience: offer step, cart, checkout with bonus applied
Problem
Users perceived trade-in offers as unfairly low and dropped off early.
Trade-in Page
Club selection
Offered price
High drop offs
Cart
Checkout
Trade-in Page
Club selection
Offered price
93% drop off
Checkout
Cart
The Trade-in flow had one huge drop-off and that was when users saw the price offered for their clubs.
The Trade-in flow had one huge drop-off and that was when users saw the price offered for their clubs.
Existing experience
Existing experience
Key insight: The company offered a 20% bonus at checkout but most users dropped off earlier.
Key insight: The business already offered a 20% trade-in bonus at checkout, but this incentive was not visible at the offer step.
Key insight: The business already offered a 20% trade-in bonus at checkout, but this incentive was not visible at the offer step.
There was no mention of the bonus at the offer step. So users dropped off without knowing the possibility of making more money from their trade-in. In the example below the user could be making $132 instead of $110.
For example:
Offer step showed $110
Final checkout value was $132
Most users dropped off before knowing the higher value existed
For example:
Offer step showed $110
Final checkout value was $132
Most users dropped off before knowing the higher value existed
Existing experience: offer step, cart, checkout with bonus applied
Existing experience: offer step, cart, checkout with bonus applied
Problem:
Users perceived trade-in offers as unfairly low and dropped off early.
Trade-in Page
Club selection
Offered price
High drop offs
Cart
Checkout
The Trade-in flow had one huge drop-off and that was when users saw the price offered for their clubs.
Existing experience
Key insight: The business already offered a 20% trade-in bonus at checkout, but this incentive was not visible at the offer step.
For example:
Offer step showed $110
Final checkout value was $132
Most users dropped off before knowing the higher value existed
Only 1% of dropped off users come back through these emails.
The strategy wasn't working for the business. the emails weren't bringing back enough users but they were making many potential sellers drop off.
Existing experience: offer step, cart, checkout with bonus applied
Strategy
Show the full price including bonuses earlier in the flow at the offer page to reduce drop offs
Option 1: Familiar and low-risk
Higher effective price, including the 20% bonus.
Simple and clear
Option 1 Mockup
Option 2: Tiered value options
Multiple trade-in options with clear differentiation and benefit explanations
1 clear highlighted “best deal” choice helping the user in decision making.
Presenting three options could increase cognitive load and potentially lead to drop-off.
Option 2 Mockup
Feasibility and developer collaboration showed option 2 to be technically complicated
Option 2 required dynamic pricing logic and that required huge effort.
Checkout could only display the base price ($110), not the bonus-inclusive price ($132)
This would create a mismatch between the offer step and checkout, increasing confusion and risk
Tiered pricing → checkout showing $110
Tiered pricing → checkout showing $110
Alternative design: Keeping the bonus structure while showing tiered options.
Showing bonuses as line-item add-ons ($110 + $22) while keeping the base price fixed ($110) at checkout
Tiered pricing showing benefits of each option
No major backend changes
Alternative solution selected → checkout
Alternative design: Keeping the bonus structure while showing tiered options.
Alternative solution selected → checkout
Alternative solution selected → checkout
Alternative solution selected → checkout
Showing bonuses as line-item add-ons ($110 + $22) while keeping the base price fixed ($110) at checkout
Tiered pricing showing benefits of each option
No major backend changes
Final decision: Implement option 1 and test option 2 as a future experiment
I presented the benefits and trade-offs of each option with stakeholders. Since we didn’t have time for usability or A/B testing, we needed to make a call with the information available.
In a fast-moving scale-up focused on revenue growth, we chose the lowest-risk path and planned to use post-launch data to validate the decision.
Implement Option 1 as the lowest-risk, fastest solution
Defer Option 2 as a future experiment once technical limitations could be addressed
I presented the benefits and trade-offs of each option with stakeholders. Since we didn’t have time for usability or A/B testing, we needed to make a call with the information available.
In a fast-moving scale-up focused on revenue growth, we chose the lowest-risk path and planned to use post-launch data to validate the decision.
Implement Option 1 as the lowest-risk, fastest solution
Defer Option 2 as a future experiment once technical limitations could be addressed
I presented the benefits and trade-offs of each option with stakeholders. Since we didn’t have time for usability or A/B testing, we needed to make a call with the information available.
In a fast-moving scale-up focused on revenue growth, we chose the lowest-risk path and planned to use post-launch data to validate the decision.
Implement Option 1 as the lowest-risk, fastest solution
Defer Option 2 as a future experiment once technical limitations could be addressed
Final design
Effective trade-in value shown upfront
Bonus clearly integrated into the offer
Reduced cognitive friction at the decision point
Results:
14%+
Users passing the offer step
8.4%+
Higher Trade-ins
Results:
14%+
Users passing the offer step
8.4%+
Higher Trade-ins
Results:
14%+
Users passing the offer step
8.4%+
Higher Trade-ins
Reflections / Results
This work was done in a scale-up environment, where speed and revenue impact were critical. At the same time, one of the companies core values was to be bold and creative, so I explored and pushed alternative concepts to improve value perception. After reviewing feasibility, risk, and timelines with product and engineering, we aligned that driving revenue quickly was the priority.
Given the size and situation of the company at the time, I believe this was the best approach. It allowed us to ship fast, improve user confidence immediately, and support short-term growth, while keeping more creative ideas as future opportunities.
Option 1: Familiar and low-risk
Option 1:
Familiar and low-risk
Higher effective price, including the 20% bonus.
Simple and clear
Option 1 Mockup
Option 1 Mockup
Option 2: Tiered value options
Option 2:
Tiered value options
Multiple trade-in options with clear differentiation and benefit explanations
1 clear highlighted “best deal” choice helping the user in decision making.
Presenting three options could increase cognitive load and potentially lead to drop-off.
Multiple trade-in options with clear differentiation and benefit explanations
1 clear highlighted “best deal” choice helping the user in decision making.
Presenting three options could increase cognitive load and potentially lead to drop-off.
Option 2 Mockup
Option 2 Mockup
Feasibility and developer collaboration showed option 2 to be technically complicated
After talking to developers I realized that option 2 Requires dynamic pricing & major back-end changes in the checkout.
So if user selects one of the options including bonus priced at $132, the checkout would only be able to show the original price at $110.
Option 2 required dynamic pricing logic and that required huge effort.
Checkout could only display the base price ($110), not the bonus-inclusive price ($132)
This would create a mismatch between the offer step and checkout, increasing confusion and risk
Option 2 required dynamic pricing logic and that required huge effort.
Checkout could only display the base price ($110), not the bonus-inclusive price ($132)
This would create a mismatch between the offer step and checkout, increasing confusion and risk
Option 2 selected → checkout showing $110
Tiered pricing → checkout showing $110
Alternative design: Keeping the bonus structure while showing tiered options.
Showing bonuses as line-item add-ons ($110 + $22) while keeping the base price fixed ($110) at checkout
Tiered pricing showing benefits of each option
No major backend changes
Tiered pricing → checkout showing $110
Alternative design: Keeping the bonus structure while showing tiered options.
Alternative solution selected → checkout
Showing bonuses as line-item add-ons ($110 + $22) while keeping the base price fixed ($110) at checkout
Tiered pricing showing benefits of each option
No major backend changes